Abstract Placing students in the most appropriate course in a language learning sequence is a perennial challenge for language educators (Fairclough, 2012a) as improper placement can lead to instructional challenges for teachers and learning difficulties for students (Arai, 2025). In 2020, ACTFL released a proficiency‐based placement test called the APPT (ACTFL Proficiency Placement Test) that is relatively inexpensive and easy to administer. However, a limited amount of research has been carried out verifying its validity and reliability. The present study attempts to remedy this by examining the use of the APPT as a placement exam in a university‐level Spanish program from the Argument Use Case (Bachman, 2005) perspective as well as the Test Development perspective (Luecht, 2003). In this study, researchers explain the process by which the items in the APPT were developed, and then compare the results of the listening portion of the APPT for students placed in various levels of university Spanish against other measures of student language ability that are relevant for placing students, such as students' self‐assessment, language learning background, and teachers' estimates of skill. Results indicate a high degree of correlation between the APPT and all these measures. Additionally, with few exceptions, the items of the APPT tended to function appropriately for their intended proficiency level. Taken together, these results suggest that the APPT is a valid and reliable proficiency‐based tool for placement.

Abstract The emergence of artificial intelligence (AI) innovations like ChatGPT presents new opportunities and challenges for world languages (WL) education. WL teacher education programs must prepare preservice teachers with AI literacy to help them effectively integrate these technologies into teaching. This multiple case study—part of our on‐going self‐study of teacher educator practice—investigated how AI literacy can be leveraged as a core practice in a WL teacher licensure program. Drawing on pre‐surveys, course artifacts, structured reflections, and interviews, the study explored how three teacher candidates (TCs) engaged with Generative AI (chatbots) in the instructional activity of lesson planning and developed emergent forms of AI literacy. Participants demonstrated varying levels of development of AI literacy across four domains: technological proficiency, pedagogical compatibility, professional work, and ethical use. They developed critical stances toward AI, which were shaped by their evolving professional identities. This study contributes to growing conversations about AI in teacher education by showing the potential of the AI literacy core practice as a scaffolded, reflective approach to building AI competencies. It also underscores the importance of centering TC's professional identity development in AI integration while providing support for prompt design, noninstructional use of AI, and facilitating conversations about responsible AI use with students.

Abstract Recent scholarship urges language educators to reconsider the purpose of language education within broader sociopolitical and sociocultural contexts, viewing language as an empowering tool to achieve shared goals for a better world. One effective approach is integrating the United Nations' Sustainable Development Goals (SDGs) into language education, enabling students to utilize the target language to address world issues they are passionate about, such as inequality and climate change, and to activate their global citizenship. However, a clear and comprehensive framework is missing to help instructors connect language education principles with the goals of Education for Sustainable Development. This paper addresses that gap by proposing the DEEP framework: Diversity, Exploration, Expression, and Partnership. This framework offers a practical guide to help teachers weave the UN's SDGs into world language through engaging, purpose‐driven projects and tasks.

Abstract World Language (WL) teacher supply has been a pervasive threat to the sustainability of K‐12 WL programs for decades; however, few studies have examined the factors that contribute to the leaky bucket. This paper presents the stories of six WL teachers in the southern United States who decided to leave the classroom despite years of experience in their schools. Their stories uncovered the interactions between teacher identity and professional agency, revealing three metaphors of high‐risk WL teachers—spare part, jack‐of‐all‐trades, and Lone Ranger. Implications for patching the leaky bucket are provided, including actions needed by stakeholders at multiple levels to ensure access to quality WL programs for all K‐12 learners.

Abstract The emergence of generative artificial intelligence (GenAI) chatbots has created opportunities and challenges for higher education. Extant scholarship has explored GenAI's capabilities and topics involving teachers' and students' perceptions of these tools. However, there is limited research exploring (1) whether second language (L2) learners actively leverage GenAI tools on their own for writing purposes in languages other than English (LOTEs), and (2) whether learners believe GenAI tools are ethical for L2 writing in educational settings. This study explores these gaps by adopting a sequential mixed methods design. First, a survey examined L2 learners (N = 287) of five LOTEs, exploring students' uses of GenAI tools for L2 writing and their beliefs about its ethicality. Second, a case study was conducted with three learners, in which interviews and video screen capture were leveraged to further understand issues of usage and ethics. The findings suggest that although many students have used GenAI tools, only 14.6% actively reported using them for L2 writing purposes. Still, such writers reported using GenAI in 12 distinct ways. Finally, 82.2% of students believed GenAI tools are ethical for different purposes. These findings are discussed with an eye toward future writing research and pedagogy.

Abstract This study investigated the differences between the ACTFL Oral Proficiency Interview (OPI) and the ACTFL Oral Proficiency Interview ‐ Computer (OPIc) among Spanish learners at a U.S. university. Participants (N = 154) were randomly assigned to take both tests in a counterbalanced order to mitigate test order effects. Data were analyzed using an aligned rank transform (ART) analysis, focusing on variables such as gender, age, language courses, missionary experience, and self‐assessed Spanish ability. Results showed a strong correlation between ACTFL OPI and ACTFL OPIc ratings (τ = 0.79, p < .001), though ACTFL OPIc ratings were slightly higher on average. No significant order effects were found, indicating the order of test administration did not influence ratings. The reliability of both tests was confirmed, and no significant biases were detected. The findings suggest that both ACTFL OPI and ACTFL OPIc are effective, holistic measures of Spanish oral proficiency, with ACTFL OPIc offering a slight advantage in rating outcomes. Pedagogically, this suggests flexibility in test choice without compromising assessment integrity.